AI discounting and pricing
We developed an AI-driven discounting and pricing system for Wehkamp to optimize warehouse utilization. The algorithm identified stagnant inventory, applying dynamic discounts and bundling strategies to clear stock efficiently. This reduced dead stock by 62% and improved margins.
Problem Identification
Wehkamp’s existing third-party dynamic pricing algorithm focused solely on demand-based price adjustments without accounting for warehouse storage costs or inventory ageing. This led to:
- Accumulation of "dead stock" occupying valuable automated warehouse space
- Storage costs eroding profit margins for stagnant items
- Missed opportunities to reallocate space for faster-selling products
Solution Overview
The custom algorithm prioritized products based on:
- Storage duration: Items exceeding predefined warehouse residency thresholds
- Cost-to-margin ratio: Products where cumulative storage costs surpassed projected sales margins
- Space utilization: Physical footprint relative to warehouse zoning requirements
Algorithm Functionality
The system employed a multi-factor approach:
Pricing Strategy Engine
- Automated discount tiers (15-70%) based on urgency metrics
- Dynamic bundling with complementary fast-moving items
- Seasonal demand forecasting integration
Key Decision Factors
| Parameter | Weight | Description |
|---|---|---|
| Holding Cost Index | 40% | Daily storage cost vs. item value |
| Demand Elasticity | 30% | Price sensitivity analysis |
| Space Criticality | 20% | Warehouse zone optimization needs |
| Seasonal Relevance | 10% | Alignment with upcoming trends |
Implementation Workflow
- Daily inventory analysis through warehouse management system APIs
- Machine learning model predicting clearance likelihood at various price points
- Automated campaign generation for flagged products
- Real-time performance monitoring with kill-switch thresholds
Outcomes
Within six months of deployment:
- Reduced stagnant inventory by 62% across three main warehouses
- Increased warehouse capacity utilization efficiency by 38%
- Improved net margins on clearance items by 17% through optimized discount staging
- Enabled 22% faster product rotation in high-value storage zones
The solution integrated seamlessly with Wehkamp’s existing robotic picking systems, creating a closed-loop inventory management ecosystem that dynamically adjusts to both market demand and operational constraints.